Descriptive discriminant analysis for repeated measures data

Background: Linear discriminant analysis (DA) encompasses procedures for classifying observations into groups (predictive discriminant analysis, PDA) and describing the relative importance of variables for distinguishing between groups (descriptive discriminant analysis, DDA) in multivariate data. In recent years, there has been increased interest in DA procedures for repeated measures data. PDA procedures that assume parsimonious repeated measures mean and covariance structures have been developed, but corresponding DDA procedures have not been proposed. Most DA procedures for repeated measures data rest on the assumption of multivariate normality, which may not be satisfied in biostatistical applications. For example, health-related quality of life (HRQOL) measures, which are increasingly being used as outcomes in clinical trials and cohort studies, are likely to exhibit skewed or heavy-tailed distributions. As well, measures of relative importance based on discriminant function coefficients (DFCs) for DDA procedures have not been proposed for repeated measures data. Purpose: The purpose of this research is to develop repeated measures discriminant analysis (RMDA) procedures based on parsimonious covariance structures, including compound symmetric and first order autoregressive structures, and that are robust (i.e., insensitive) to multivariate non-normal distributions. It also extends these methods to evaluate the relative importance of variables in multivariate repeated measures (i.e., doubly multivariate) data. Method: Monte Carlo studies were conducted to investigate the performance of the proposed RMDA procedures under various degrees of group mean separation, repeated measures correlation structures, departure from multivariate normality, and magnitude of covariance mis-specification. Data from the Manitoba Inflammatory Bowel Disease Cohort Study, a prospective longitudinal cohort study about the psychosocial determinants of health and well-being, are used to illustrate their applications. Results: The conventional maximum likelihood (ML) estimates of DFCs for RMDA procedures based on parsimonious covariance structures exhibited substantial bias and error when the covariance structure was mis-specified or when the data followed a multivariate skewed or heavy-tailed distribution. The DFCs of RMDA procedures based on robust estimators obtained from coordinatewise trimmed means and Winsorized variances, were less biased and more efficient when the data followed a multivariate non-normal distribution, but were sensitive to the effects of covariance mis-specification. Measures of relative importance for doubly multivariate data based on linear combinations of the within-variable DFCs resulted in the highest proportion of correctly ranked variables. Conclusions: DA procedures based on parsimonious covariance structures and robust estimators will produce unbiased and efficient estimates of variable relative importance of variables in repeated measures data and can be used to test for change in relative importance over time. The choice among these RMDA procedures should be guided by preliminary descriptive assessments of the data

DEPTH-BASED CLASSIFICATION FOR FUNCTIONAL DATA

Classification is an important task when data are curves. Recently, the notion of statistical depth has been extended to deal with functional observations. In this paper, we propose robust procedures based on the concept of depth to classify curves. These techniques are applied to a real data example. An extensive simulation study with contaminated models illustrates the good robustness properties of these depth-based classification methods.

Professional issues in maternal mental health scale (PIMMHS): The development and initial validation of a brief and valid measure

Introduction:The life-threatening consequences of perinatal mental health problems (PMHP) are well documented. Midwives are ideally placed to effectively identify women at risk and facilitate early intervention. However, a multitude of factors contribute to failure in recognition and treatment. It would be of value for service providers to be able to identify key professional issues in their own context. The present study sought to develop and evaluate a ‘professional issues in maternal mental health’ scale (PIMMHS), explore its psychometric properties and potential application.Methods:A cross-sectional design and instrument evaluation approach was taken to investigate the psychometric properties of the PIMMHS. A total of 266 student midwives from 10 UK institutions completed the PIMMHS via Survey Monkey.Results:PIMMHS comprises two sub-scales of emotion/communication (PIMMHSEmotion sub-scale) and training (PIMMHS-Training sub-scale). Both PIMMHS subscales demonstrate adequate divergent and convergent validity. Sub-optimal internal consistency was observed for the training sub-scale, however, the PIMMHS-Training had a more impressive effect size in terms of known-groups discriminant validity compared to PIMMHS-Emotion.Conclusions:The PIMMHS appears to be a sound psychometric instrument for assessing professional issues that influence the practice of student midwives in PMH. The PIMMHS could support education providers to identify areas for curriculum development, as well as maternity services in proactive assessment of service provision, to identify training and service development opportunities

Psychological Need Thwarting in the Sport Context: Assessing the Darker Side of Athletic Experience

Research in self-determination theory (Ryan & Deci, 2002) has shown that satisfac­tion of autonomy, competence, and relatedness needs in sport contexts is associated with enhanced engagement, performance, and well-being. This article outlines the initial development of a multidimensional measure designed to assess psychologi­cal need thwarting, an under-studied area of conceptual and practical importance. Study 1 generated a pool of items designed to tap the negative experiential state that occurs when athletes perceive their needs for autonomy, competence, and relatedness to be actively undermined. Study 2 tested the factorial structure of the questionnaire using confirmatory factor analysis. The supported model comprised 3 factors, which represented the hypothesized interrelated dimensions of need thwarting. The model was refined and cross-validated using an independent sample in Study 3. Overall, the psychological need thwarting scale (PNTS) demonstrated good content, factorial, and predictive validity, as well as internal consistency and invariance across gender, sport type, competitive level, and competitive experi­ence. The conceptualization of psychological need thwarting is discussed, and suggestions are made regarding the use of the PNTS in research pertaining to the darker side of sport participation

Nonlinear heart rate variability features for real-life stress detection. Case study : students under stress due to university examination

Background: This study investigates the variations of Heart Rate Variability (HRV) due to a real-life stressor and proposes a classifier based on nonlinear features of HRV for automatic stress detection. Methods: 42 students volunteered to participate to the study about HRV and stress. For each student, two recordings were performed: one during an on-going university examination, assumed as a real-life stressor, and one after holidays. Nonlinear analysis of HRV was performed by using Poincaré Plot, Approximate Entropy, Correlation dimension, Detrended Fluctuation Analysis, Recurrence Plot. For statistical comparison, we adopted the Wilcoxon Signed Rank test and for development of a classifier we adopted the Linear Discriminant Analysis (LDA). Results: Almost all HRV features measuring heart rate complexity were significantly decreased in the stress session. LDA generated a simple classifier based on the two Poincaré Plot parameters and Approximate Entropy, which enables stress detection with a total classification accuracy, a sensitivity and a specificity rate of 90%, 86%, and 95% respectively. Conclusions: The results of the current study suggest that nonlinear HRV analysis using short term ECG recording could be effective in automatically detecting real-life stress condition, such as a university examination

Logopenic and nonfluent variants of primary progressive aphasia are differentiated by acoustic measures of speech production

Differentiation of logopenic (lvPPA) and nonfluent/agrammatic (nfvPPA) variants of Primary Progressive Aphasia is important yet remains challenging since it hinges on expert based evaluation of speech and language production. In this study acoustic measures of speech in conjunction with voxel-based morphometry were used to determine the success of the measures as an adjunct to diagnosis and to explore the neural basis of apraxia of speech in nfvPPA. Forty-one patients (21 lvPPA, 20 nfvPPA) were recruited from a consecutive sample with suspected frontotemporal dementia. Patients were diagnosed using the current gold-standard of expert perceptual judgment, based on presence/absence of particular speech features during speaking tasks. Seventeen healthy age-matched adults served as controls. MRI scans were available for 11 control and 37 PPA cases; 23 of the PPA cases underwent amyloid ligand PET imaging. Measures, corresponding to perceptual features of apraxia of speech, were periods of silence during reading and relative vowel duration and intensity in polysyllable word repetition. Discriminant function analyses revealed that a measure of relative vowel duration differentiated nfvPPA cases from both control and lvPPA cases (r2 = 0.47) with 88% agreement with expert judgment of presence of apraxia of speech in nfvPPA cases. VBM analysis showed that relative vowel duration covaried with grey matter intensity in areas critical for speech motor planning and programming: precentral gyrus, supplementary motor area and inferior frontal gyrus bilaterally, only affected in the nfvPPA group. This bilateral involvement of frontal speech networks in nfvPPA potentially affects access to compensatory mechanisms involving right hemisphere homologues. Measures of silences during reading also discriminated the PPA and control groups, but did not increase predictive accuracy. Findings suggest that a measure of relative vowel duration from of a polysyllable word repetition task may be sufficient for detecting most cases of apraxia of speech and distinguishing between nfvPPA and lvPPA